chore: import upstream snapshot with attribution
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This commit is contained in:
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# Tokenspeed-kernel Plugin System
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> **Status: experimental.** The plugin contract — entry-point group name,
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> `register()` signature, `KernelSpec` fields, selection priority semantics,
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> and the `tokenspeed_kernel.plugins` Python API — may change without
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> backwards-compatibility guarantees while we shake the design out. Pin to
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> an exact `tokenspeed-kernel` version in your plugin's dependencies.
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This subpackage lets third-party packages register kernel implementations
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into the global `KernelRegistry` without modifying `tokenspeed-kernel`
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itself.
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## How it works
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1. Your plugin package exposes a `register()` function that calls
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`tokenspeed_kernel.registry.register_kernel(...)` (or
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`KernelRegistry.get().register(...)`) for each kernel it provides.
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2. Your `pyproject.toml` advertises that function under the
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`tokenspeed_kernel.plugins` entry-point group.
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3. The host application (engine, benchmark, notebook, etc.) calls
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`tokenspeed_kernel.plugins.discover_plugins()` once at startup, after
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built-in kernels have been imported. Discovery walks the entry-point
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group and invokes each `register()`.
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Loading is **fully explicit** — importing `tokenspeed_kernel` or
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`tokenspeed_kernel.plugins` does **not** trigger discovery on its own.
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## Example plugin
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A minimal out-of-tree package that contributes a custom decode-attention
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kernel for NVIDIA Hopper.
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```
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my-kernels-plugin/
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├── pyproject.toml
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└── my_kernels_plugin/
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└── __init__.py
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```
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`my_kernels_plugin/__init__.py`:
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```python
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import torch
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from tokenspeed_kernel.platform import ArchVersion, CapabilityRequirement
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from tokenspeed_kernel.signature import format_signatures
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from tokenspeed_kernel.registry import register_kernel
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def register() -> None:
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"""Entry point invoked by tokenspeed_kernel.plugins.discover_plugins()."""
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@register_kernel(
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"attention",
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"decode",
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solution="my_custom",
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signatures=format_signatures(
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("q", "k_cache", "v_cache"), "dense", {torch.bfloat16}
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),
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capability=CapabilityRequirement(
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vendors=frozenset({"nvidia"}),
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min_arch_version=ArchVersion(9, 0),
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),
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# Built-in FlashInfer decode is priority 18; pick 19 to win selection.
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priority=19,
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)
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def my_custom_attn_decode(q, kv_cache, page_table, seq_lens, **kwargs):
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...
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```
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`pyproject.toml`:
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```toml
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[project]
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name = "my-kernels-plugin"
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version = "0.1.0"
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# Pin tightly while the plugin contract is experimental.
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dependencies = ["tokenspeed-kernel==<exact-version>"]
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[project.entry-points."tokenspeed_kernel.plugins"]
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my_plugin = "my_kernels_plugin:register"
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```
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Install and load:
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```bash
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pip install -e ./my-kernels-plugin
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```
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```python
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import tokenspeed_kernel # registers built-in kernels
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from tokenspeed_kernel.plugins import discover_plugins, list_plugins
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discover_plugins()
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print(list_plugins()) # -> [PluginInfo(name='my_plugin', ...)]
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```
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## Host-application integration
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Engines and other long-running hosts should call `discover_plugins()`
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exactly once at startup, after built-in kernel modules have been imported
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(so plugins can override built-ins by registering at a higher priority).
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```python
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import tokenspeed_kernel # noqa: F401 -- registers built-ins
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from tokenspeed_kernel.plugins import discover_plugins
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discover_plugins()
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```
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For ad-hoc use (notebooks, scripts, tests), there is no need to use entry
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points at all — call `register_kernel(...)` directly:
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```python
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import torch
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from tokenspeed_kernel.signature import format_signatures
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from tokenspeed_kernel.registry import register_kernel
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@register_kernel(
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"gemm",
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"mm",
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solution="experiment",
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signatures=format_signatures(("a", "b"), "dense", {torch.bfloat16}),
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priority=15,
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)
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def my_experimental_gemm(a, b, **kwargs):
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...
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```
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## Disabling plugins
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Plugins can be skipped without uninstalling them:
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```bash
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TOKENSPEED_KERNEL_DISABLE_PLUGINS="my_plugin,other_plugin" python ...
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```
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```python
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from tokenspeed_kernel.plugins import disable_plugin, discover_plugins
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disable_plugin("my_plugin")
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discover_plugins()
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```
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The names refer to entry-point names (the left-hand side of the
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`[project.entry-points."tokenspeed_kernel.plugins"]` table), not
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distribution names.
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## Inspection
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```bash
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python -m tokenspeed_kernel.plugins list
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python -m tokenspeed_kernel.plugins info my_plugin
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```
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```python
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from tokenspeed_kernel.plugins import list_plugins
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for info in list_plugins():
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print(info.name, info.version, info.kernel_names)
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```
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## Selection contract
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- Priority is an integer in `[0, 20)`. Higher wins. The reference
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implementation lives at `0`. Built-in optimized kernels typically sit at
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`10`–`18`. Plugin authors who want to override a built-in should choose
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a value strictly higher than the built-in they replace.
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- `discover_plugins()` walks entry points in alphabetical order by
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entry-point name. When two registrations land at the same priority for
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the same `(family, mode)`, the warning is emitted and selection becomes
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load-order-dependent — set explicit, distinct priorities to avoid this.
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- A plugin whose `register()` raises does not crash discovery; a
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`UserWarning` is emitted and other plugins continue loading.
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## Failure modes worth knowing
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- **No discovery call → no plugin kernels.** Forgetting to call
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`discover_plugins()` is silent.
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- **Plugin loaded before built-ins.** If you call `discover_plugins()`
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before `import tokenspeed_kernel`, plugins that intend to override
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built-ins will appear to win, but the built-in modules will be imported
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later and may overwrite the plugin's slot. Always import
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`tokenspeed_kernel` first.
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- **Stale registry.** Calling `KernelRegistry.reset()` clears registered
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kernels but leaves `_loaded_plugins` populated; re-discovery will skip
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already-loaded plugins. Use `discover_plugins(force=True)` after a
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reset.
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